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czso

CRAN status CRAN downloads CRAN monthly downloads Lifecycle: maturing Mentioned in Awesome Official Statistics R-CMD-check

The goal of czso is to provide direct, programmatic, hassle-free access from R to open data provided by the Czech Statistical Office (CZSO).

This is done by

  1. providing direct access from R to the catalogue of open CZSO datasets, eliminating the hassle from data discovery. Normally this is done done through the CZSO’s product catalogue which is unfortunately a bit clunky, or data.gov.cz, which is not a natural starting point for many.

  2. providing a function to load a specific dataset to R directly from the CZSO’s datastore, eliminating the friction of copying a URL, downloading, unzipping etc.

Additionally, the package provides access to metadata on datasets and to codelists (číselníky) as a special case of datasets listed in the catalogue.

Installation

You can install the package from CRAN:

install.packages("czso")

You can install the latest in-development release from github with:

remotes::install_github("petrbouchal/czso", ref = github_release())

or the latest version with:

remotes::install_github("petrbouchal/czso")

I also keep binaries in a drat repo, which you can access by

install.packages("czso", repos = "https://petrbouchal.xyz/drat")

Example

Say you are looking for a dataset whose title refers to wages (mzda/mzdy):

First, retrieve the list of available CZSO datasets:

library(czso)
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(stringr))

catalogue <- czso_get_catalogue()

Now search for your terms of interest in the dataset titles:

catalogue %>% 
  filter(str_detect(title, "[Mm]zd[ay]")) %>% 
  select(dataset_id, title, description)
#> # A tibble: 2 × 3
#>   dataset_id title                                                   description
#>   <chr>      <chr>                                                   <chr>      
#> 1 110080     Průměrná hrubá měsíční mzda a medián mezd v krajích     Datová sad…
#> 2 110079     Zaměstnanci a průměrné hrubé měsíční mzdy podle odvětví Datová sad…

You could also search in descriptions or keywords which are also retrieved into the catalogue.

We can see the dataset_id for the required dataset - now use it to get the dataset:

czso_get_table("110080")
#> # A tibble: 1,080 × 14
#>    idhod  hodnota stapro_kod SPKVANTIL_cis SPKVANTIL_kod POHLAVI_cis POHLAVI_kod
#>    <chr>    <dbl> <chr>      <chr>         <chr>         <chr>       <chr>      
#>  1 73662…   21782 5958       7636          Q5            <NA>        <NA>       
#>  2 73662…   25625 5958       <NA>          <NA>          <NA>        <NA>       
#>  3 73662…   28431 5958       <NA>          <NA>          102         1          
#>  4 73662…   22133 5958       <NA>          <NA>          102         2          
#>  5 73662…   23533 5958       7636          Q5            102         1          
#>  6 73662…   19731 5958       7636          Q5            102         2          
#>  7 74595…   26033 5958       <NA>          <NA>          <NA>        <NA>       
#>  8 74595…   28873 5958       <NA>          <NA>          102         1          
#>  9 74595…   22496 5958       <NA>          <NA>          102         2          
#> 10 74595…   21997 5958       7636          Q5            <NA>        <NA>       
#> # ℹ 1,070 more rows
#> # ℹ 7 more variables: rok <int>, uzemi_cis <chr>, uzemi_kod <chr>,
#> #   STAPRO_TXT <chr>, uzemi_txt <chr>, SPKVANTIL_txt <chr>, POHLAVI_txt <chr>

You can retrieve the schema for the dataset:

czso_get_table_schema("110080")
#> # A tibble: 14 × 5
#>    name          titles        `dc:description`                required datatype
#>    <chr>         <chr>         <chr>                           <lgl>    <chr>   
#>  1 idhod         idhod         "unikátní identifikátor údaje … TRUE     string  
#>  2 hodnota       hodnota       "zjištěná hodnota"              TRUE     number  
#>  3 stapro_kod    stapro_kod    "kód statistické proměnné ze s… TRUE     string  
#>  4 spkvantil_cis spkvantil_cis "kód číselníku pro kvantil"     TRUE     string  
#>  5 spkvantil_kod spkvantil_kod "kód položky z číselníku pro k… TRUE     string  
#>  6 pohlavi_cis   pohlavi_cis   "kód číselníku pro pohlaví"     TRUE     string  
#>  7 pohlavi_kod   pohlavi_kod   "kód položky číselníku pro poh… TRUE     string  
#>  8 rok           rok           "rok referenčního období ve fo… TRUE     number  
#>  9 uzemi_cis     uzemi_cis     "kód číselníku pro referenční … TRUE     string  
#> 10 uzemi_kod     uzemi_kod     "kód položky číselníku pro ref… TRUE     string  
#> 11 uzemi_txt     uzemi_txt     "text položky z číselníku pro … TRUE     string  
#> 12 stapro_txt    stapro_txt    "text statistické proměnné"     TRUE     string  
#> 13 spkvantil_txt spkvantil_txt "text položky číselníku pro kv… TRUE     string  
#> 14 pohlavi_txt   pohlavi_txt   "text položky číselníku pro po… TRUE     string

and download the documentation in PDF:

czso_get_dataset_doc("110080", action = "download", format = "pdf")
#> ✔ Downloaded <https://www.czso.cz/documents/62353418/171419376/110080-22dds.pdf> to '110080-22dds.pdf'

If you are interested in linking this data to different data, you might need the NUTS codes for regions. Seeing that the lines with regional breakdown list uzemi_cis as "100", you can get that codelist (číselník):

czso_get_codelist(100)
#> # A tibble: 15 × 11
#>    kodjaz akrcis  kodcis chodnota zkrtext text  admplod admnepo cznuts kod_ruian
#>    <chr>  <chr>   <chr>  <chr>    <chr>   <chr> <chr>   <chr>   <chr>  <chr>    
#>  1 CS     KRAJ_N… 100    3000     Extra-… Extr… 2004-0… 9999-0… CZZZZ  <NA>     
#>  2 CS     KRAJ_N… 100    3018     Hl. m.… Hlav… 2001-0… 9999-0… CZ010  19       
#>  3 CS     KRAJ_N… 100    3026     Středo… Stře… 2001-0… 9999-0… CZ020  27       
#>  4 CS     KRAJ_N… 100    3034     Jihoče… Jiho… 2001-0… 9999-0… CZ031  35       
#>  5 CS     KRAJ_N… 100    3042     Plzeňs… Plze… 2001-0… 9999-0… CZ032  43       
#>  6 CS     KRAJ_N… 100    3051     Karlov… Karl… 2001-0… 9999-0… CZ041  51       
#>  7 CS     KRAJ_N… 100    3069     Ústeck… Úste… 2001-0… 9999-0… CZ042  60       
#>  8 CS     KRAJ_N… 100    3077     Libere… Libe… 2001-0… 9999-0… CZ051  78       
#>  9 CS     KRAJ_N… 100    3085     Králov… Král… 2001-0… 9999-0… CZ052  86       
#> 10 CS     KRAJ_N… 100    3093     Pardub… Pard… 2001-0… 9999-0… CZ053  94       
#> 11 CS     KRAJ_N… 100    3107     Kraj V… Kraj… 2001-0… 9999-0… CZ063  108      
#> 12 CS     KRAJ_N… 100    3115     Jihomo… Jiho… 2001-0… 9999-0… CZ064  116      
#> 13 CS     KRAJ_N… 100    3123     Olomou… Olom… 2001-0… 9999-0… CZ071  124      
#> 14 CS     KRAJ_N… 100    3131     Zlínsk… Zlín… 2001-0… 9999-0… CZ072  141      
#> 15 CS     KRAJ_N… 100    3140     Moravs… Mora… 2001-0… 9999-0… CZ080  132      
#> # ℹ 1 more variable: zkrkraj <chr>

You would then need to do a bit of manual work to join this codelist onto the data.

A note about “tables” and “datasets”

In the parlance of the official open data catalogue, a dataset can have multiple distributions (typically multiple formats of the same data). These are called resources in the internals, and manifest as tables in this package. Some metainformation is the property of a dataset (the documentation), while other - the schema - is the property of a table. Hence the function names in this package. This is to keep things organised even if the CZSO almost always provides only one table per dataset and appends new data to it over time.

Data sources

The catalogue is drawn from https://data.gov.cz through the SPARQL endpoint.

The data and specific metadata is then accessed via the package_show endpoint of the CZSO API at (example) https://vdb.czso.cz/pll/eweb/package_show?id=290038r19.

Credit and notes

Acknowledgments

Thanks to @jakubklimek and @martinnecasky for helping me figure out the SPARQL endpoint on the Czech National Open Data Catalogue.

An homage to the CZSO’s work in releasing its data in an open format, something that is not necessarily in its DNA.

It alludes to the shades of the country reflected in the tabular data provided, By interspersing the comma symbol into the name of the package, it refers to both integration between statistics and open data and the slight disruption that the world of statistics undergoes when that integration happens.

See also

This package takes inspiration from the packages

which are very useful in their own right - much recommended.

For Czech geospatial data, see CzechData by JanCaha.

For Czech fiscal data, see statnipokladna.

For various transparency disclosures, see Hlídač státu and the {hlidacr} package.

For access to some of Prague’s open geospatial data in R, see pragr.

Contributing / code of conduct

Please note that the ‘czso’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.